Spatial and genetic epidemiology of hookworm in a rural community in Uganda

Abstract

There are remarkably few contemporary, population-based studies of intestinal nematode infection for sub-Saharan Africa. This paper presents a comprehensive epidemiological analysis of hookworm infection intensity in a rural Ugandan community. Demographic, kinship, socioeconomic and environmental data were collected for 1,803 individuals aged six months to 85 years in 341 households in a cross-sectional community survey. Hookworm infection was assessed by faecal egg count. Spatial variation in the intensity of infection was assessed using a Bayesian negative binomial spatial regression model and the proportion of variation explained by host additive genetics (heritability) and common domestic environment was estimated using genetic variance component analysis. Overall, the prevalence of hookworm was 39.3%, with the majority of infections (87.7%) of light intensity (<or=1000 eggs per gram faeces). Intensity was higher among older individuals and was associated with treatment history with anthelmintics, walking barefoot outside the home, living in a household with a mud floor and education level of the household head. Infection intensity also exhibited significant household and spatial clustering: the range of spatial correlation was estimated to be 82 m and was reduced by a half over a distance of 19 m. Heritability of hookworm egg count was 11.2%, whilst the percentage of variance explained by unidentified domestic effects was 17.8%. In conclusion, we suggest that host genetic relatedness is not a major determinant of infection intensity in this community, with exposure-related factors playing a greater role.

Figure 1. Representation of the relationships between peri-domestic, household and individual variables and hookworm burden.

Includes the areas of this framework addressed by complementary analysis strategies used in this paper. For example, socio-economic factors (assessed, for example, by asset ownership) act through a number of inter-related proximate determinants, which include environmental factors (such as availability of water and sanitation), behavioural factors (such as health seeking behaviours) and nutrition (including anthropometric status and diet) which in turn may affect the risk of an individual being infected with hookworm. Covariates with available data are underlined. Both analyses address hookworm intensity (epg): the spatial analysis uses a negative binomial model, incorporating an over dispersion parameter (k) to account for extra-Poisson variation; quantitative genetic analysis (genetic variance component analysis) uses a linear regression model, therefore data was log-transformed prior to analysis. These methods both exploit correlation structures in egg counts: for example, if there is a genetic basis to susceptibility, correlation due to genetic effects may be expected to decrease with distance in the pedigree, whereas if exposure to infective hookworm larvae most commonly occurs outside the household (for example in agricultural areas or defined defecation sites away from the household [42]), correlation due to environmental effects may decrease slowly with physical distance between households.

Figure 2. Age-sex distributions for hookworm infection.

(A) prevalence of hookworm infection, (B) mean intensity of infection, in epg, and (C) median intensity of infection (in epg) for those infected only (dashed lines indicate the population interquartile range). Males, closed circles; Females, open circles.

Figure 3. Map of the small-scale spatial heterogeneity of hookworm intensity in Mulanda, after adjusting for individual and household risk factors.

Each dot represents a compound, with the shading showing the quartile of the standardised parasite ratio (SPR; ratio by which the compound's mean log egg count is higher or lower than expected) as derived by the Bayesian spatial model. High infection intensities are seen in the south-west, north-west and east of the study site, whilst low intensity infections are seen in the central region. Inset: location of the study site in eastern Uganda.